Explicit discrimination and health: development and psychometric properties of an assessment instrument
Discriminação explícita e saúde: desenvolvimento e propriedades psicométricas de um instrumento
Discriminación explícita y salud: desarrollo y propiedades psicométricas de un instrumento
João Luiz BastosI; Eduardo FaersteinII; Roger Keller CelesteIII; Aluisio J D BarrosIV
IDepartamento de Saúde Pública. Centro de Ciências da Saúde. Universidade Federal de Santa Catarina. Florianópolis, SC, Brasil
IIDepartamento de Epidemiologia. Instituto de Medicina Social. Universidade do Estado do Rio de Janeiro. Rio de Janeiro, RJ, Brasil
IIIDepartamento de Odontologia Preventiva e Social. Faculdade de Odontologia. Universidade Federal do Rio Grande do Sul. Porto Alegre, RS, Brasil
IVDepartamento de Medicina Social. Faculdade de Medicina. Universidade Federal de Pelotas. Pelotas, RS, Brasil
OBJECTIVE: To develop an instrument to assess discrimination effects on health outcomes and behaviors, capable of distinguishing harmful differential treatment effects from their interpretation as discriminatory events.
METHODS: Successive versions of an instrument were developed based on a systematic review of instruments assessing racial discrimination, focus groups and review by a panel comprising seven experts. The instrument was refined using cognitive interviews and pilot-testing. The final version of the instrument was administered to 424 undergraduate college students in the city of Rio de Janeiro, Southeastern Brazil, in 2010. Structural dimensionality, two types of reliability and construct validity were analyzed.
RESULTS: Exploratory factor analysis corroborated the hypothesis of the instrument's unidimensionality, and seven experts verified its face and content validity. The internal consistency was 0.8, and test-retest reliability was higher than 0.5 for 14 out of 18 items. The overall score was higher among socially disadvantaged individuals and correlated with adverse health behaviors/conditions, particularly when differential treatments were attributed to discrimination.
CONCLUSIONS: These findings indicate the validity and reliability of the instrument developed. The proposed instrument enables the investigation of novel aspects of the relationship between discrimination and health.
Descriptors: Prejudice. Interpersonal Relations. Socioeconomic Factors. Health Inequalities.
OBJETIVO: Desenvolver instrumento para avaliar os efeitos de experiências discriminatórias sobre condições e comportamentos em saúde, capaz de distinguir efeitos patológicos da exposição a tratamentos diferenciais de sua interpretação como eventos discriminatórios.
MÉTODOS: Versões sucessivas do instrumento foram elaboradas com base em uma revisão sistemática da literatura sobre escalas de discriminação, grupos focais e apreciação por um painel de sete especialistas. O refinamento do instrumento foi atingido por meio de entrevistas cognitivas e estudo-piloto, de modo que sua versão final foi aplicada em 424 estudantes de graduação no Rio de Janeiro, RJ, em 2010. A estrutura dimensional, dois tipos de confiabilidade e validade de construto foram avaliadas.
RESULTADOS: A análise fatorial exploratória corroborou a hipótese de unidimensionalidade do instrumento e sete especialistas indicaram que este apresentava validade de face e conteúdo. A consistência interna foi de 0,8 e a confiabilidade teste-reteste foi maior do que 0,5 para 14 dos 18 itens. O escore foi estatisticamente mais alto em indivíduos socialmente desprivilegiados e associou-se com comportamentos/condições de saúde adversos, especialmente quando tratamentos atribuídos à discriminação foram considerados.
CONCLUSÕES: Estes resultados sugerem validade e confiabilidade do instrumento desenvolvido. A escala apresentada permitirá investigar aspectos inovadores das relações entre discriminação e saúde.
Descritores: Preconceito. Relações Interpessoais. Fatores Socioeconômicos. Desigualdades em Saúde.
OBJETIVO: Desarrollar instrumento para evaluar los efectos de experiencias discriminatorias sobre condiciones y comportamientos en salud, distinguiendo efectos patológicos de la exposición a tratamientos diferenciales de su interpretación como eventos discriminatorios.
MÉTODOS: Versiones sucesivas del instrumento fueron elaboradas con base en una revisión sistemática de la literatura sobre escalas de discriminación, grupos focales y apreciación por un panel de siete especialistas. El refinamiento del instrumento fue alcanzado por medio de entrevistas cognitivas y estudio piloto, de modo que la versión final fue aplicada en 424 estudiantes de pregrado en Rio de Janeiro, sureste de Brasil, en 2010. La estructura dimensional, dos tipos de confiabilidad y validez del constructo fueron evaluadas.
RESULTADOS: El análisis factorial exploratorio corroboró la hipótesis de unidimensionalidad del instrumento y siete especialistas indicaron que el presentaba validez de orientación y contenido. La consistencia interna fue de 0,8 y la confiabilidad de la prueba y re-evaluación fue mayor a 0,5 para 14 de los 18 itens. El escore general fue más alto en individuos socialmente desafortunados y se asoció con comportamientos/condiciones de salud adversos, especialmente al considerarse tratamientos atribuidos a la discriminación.
CONCLUSIONES: Estos resultados sugieren validez y confiabilidad del instrumento desarrollado. La escala presentada permitirá investigar aspectos innovadores de las relaciones entre discriminación y salud.
Descriptores: Prejuicio. Relaciones Interpersonales. Factores Socioeconómicos. Desigualdades en la Salud.
The discrimination construct is closely related to the idea of injustice and, as such, has been conceptualized as the "process by which a member, or members, of a socially defined group is, or are, treated differently (especially unfairly) because of his/ her/ their membership of that group."15 It has been studied worldwide in several fields of knowledge, such as anthropology, epidemiology, sociology and psychology, with extensive literature documenting important discrimination effects on people's daily lives. For instance, discrimination has been associated with negative health outcomes,25difficult access to the labor market,6 and residential segregation.25
Discriminatory practices may be based on characteristics such as gender, age, physical appearance, race, ethnicity, social class, and other socially ascribed or acquired characteristics. These multiple types of discrimination may also be combined and experienced all at once by their victims.4 Yet, discriminatory practices and their behavioral and cognitive responses may vary depending on the social context and historical time period.
A systematic review of instruments assessing racial discrimination3 found no widely employed instrument that has been adapted for use in different sociocultural backgrounds. Almost all instruments have been recently developed, mainly in the United States (U.S.), and are in early stages of construction and refinement. In addition, most instruments have been developed for use in specific population groups such as U.S. schoolchildren and self-classified black women, and they address specific aspects of discrimination or different constructs simultaneously, e.g., racism, prejudice and discrimination per se.
In spite of social and historical specificities, discrimination may be viewed as a universal construct, with common aspects and forms of manifestation in different population groups. And the development of instruments for assessing discrimination potentially adaptable to different sociocultural backgrounds is a relevant goal. These initiatives are aligned with a universalist approach,23 which posits that "basic psychological processes are likely to be commom features of human life everywhere, but their manifestations are likely to be influenced by culture. [...] Methodologically, comparisons are employed, but cautiously, [and] assessment procedures are likely to require modification"5 from one context to another.
This study aimed to develop and psychometrically assess an instrument addressing lifetime experiences of discrimination considering different life domains and a range of possible motivations. The instrument is also intended to be potentially adaptable to different contexts and population groups based on the aforementioned universalist approach.
The study adopts an intersectionality perspective,8 in which different types of discrimination (e.g., race and gender discrimination) may interact and may be experienced at the same time. This instrument was designed to assess discriminatory experiences at an interpersonal level, with a focus on behaviors resulting from intentional cognitive processes of their perpetrators.19 The instrument assesses only explicit discrimination, conceptualized as isolated acts of discrimination of a single individual who discriminates against others based on personal prejudice.19 Explicit discrimination may manifest itself as a set of behaviors of varying intensities,7 including verbal antagonism and avoidance, as well as segregation, physical attacks and extermination of groups or individuals. According to Blank et al7 (2004), explicit discrimination may occur within five different life domains: labor market; educational system; housing/mortgage lending; criminal justice and health services. Discriminatory practices in each of these domains are seen mainly regarding access to institutions, performance and evaluation of certain tasks and advancement to higher levels or stages, involving perpetrators that are specific to these settings.
Prior to the development of a preliminary set of items, a systematic literature review3 was conducted to describe and review psychometric properties of instruments for assessing racial discrimination. This review showed that none of the reviewed instruments consider the attribution of differential treatments to discrimination as a primary appraisal of threat in one's environment, as previously proposed in the literature.18 The attribution of differential treatment to discrimination (whether an event has the potential for harm or loss) was examined. Therefore, the experience of differential treatment and its attribution to discrimination were devised to be recorded separately, by different items of the present instrument, allowing to answering the following research question: Are the health effects of discrimination a consequence of the reported differential treatment or its attribution to discrimination by stigmatized individuals?
In addition to the literature review, a qualitative study4 helped drafting the items. Meanings attributed by college students to discrimination and prejudice were assessed in order to grasp the relevance of these constructs within this sociocultural background. The reported experiences of discrimination, life situations in which they occurred, and their association with the five domains proposed by Blank et al7 (2004) were also investigated.
Based on the qualitative study4 and the literature review3 a preliminary set of items was developed. The first version comprised 28 items, which were discussed individually with seven experts (six Brazilians and one American) between November and December 2009. The experts were senior researchers in public health, psychology, and anthropology, and they reviewed the format and content of the items, as well as the face and content validity of the instrument as a whole.
Although the development of items regarding specific life events may negatively affect content validity, this approach was used to address the phenomenon of intra-category variability, i.e., incorrect grouping of discrimination experiences that reflect different manifestations of the phenomenon.10 Terms such as racism, discrimination, race, prejudice, among others, were not used in the formulation of the instrument's items to minimize the emotional impact on respondents while addressing such a sensitive topic.
Respondents are inquired about their experiences of specific negative differential treatments, without defining a recall period. Items were developed to reflect the construct map outlined above, as well as reports by focus groups in the qualitative phase of the study. However, items were not arranged according to a theoretical gradient of intensity specified in the construct map; for example, it was assumed that respondents would first answer items on physical aggression, and then on verbal antagonism because this would sound more natural, resembling the way different experiences of discrimination were reported in focus group sessions. The answers to these items are recorded on a 4-point Likert scale: "none" (0); "rarely" (1); "several times" (2); and "always" (3). Those respondents answering "yes" to the questions on negative differential treatments are asked three additional subitems for each of the situations reported. The first subitem includes one or more motivations for differential treatment (e.g., socioeconomic position; race; physical disability) and the other two investigate the level of discomfort caused and the attribution of the reported event to discrimination. The level of discomfort caused by the differential treatment is measured on a 4-point Likert scale ("low;" "intermediate;" "high," and "very high"), while the attribution of the differential treatment to discrimination is measured dichotomously (no/yes).
Four pre-testing sessions were carried out using preliminary versions of the instrument involving 10 undergraduate college students in social sciences from a public university in Rio de Janeiro, Southeastern Brazil, in March 2010. A cognitive interviewing technique was applied and pre-test sessions were conducted as follows: (1) respondents were asked to paraphrase all items of the instrument and to define the meaning of specific terms, such as discrimination, prejudice and discomfort; (2) the process used in response formulation was explored, with particular attention to any difficulties in choosing the most appropriate answer options; and (3) assessment of how easy to understand the general instructions were, and how respondents dealt with questions that should be left blank or skipped.
The instrument was revised based on the findings of the cognitive interviews and a pilot-study carried out with 15 students from different areas at the same university. A final version was produced and applied to a larger group of 424 university students. The instrument for assessing discrimination was designed as a section of a self-administered questionnaire that also provided information on smoking, alcohol use (based on the Alcohol Use Disorders Identification Test - AUDIT),1 self-reported health status, common mental disorders (based on the General Health Questionnaire),12 socioeconomic status (based on the Brazilian National Wealth Score - IEN),2 parental education, gender, age and self-reported skin color/race (based on the Brazilian Institute of Geography and Statistics categories). Other information included marital status, course attended and whether college admission was through a quota system. Access to this university is through an entrance exam, where 45% of places are reserved for students self-reported as black, with mixed skin color or indigenous, who come from public schools, have disabilities, and are children of policemen, firefighters, security agents and prison administration officers killed or disabled in service. Another self-administered questionnaire including only items on experiences of discrimination was applied 15 days later in 13% (n=55) of the students to estimate the instrument's test-retest reliability.
Participants were selected based on a survey conducted in 2008. This is an electronic survey carried out twice a year as part of the students' registration process that provides detailed data on skin color/race, gender, parental education, and age. The analysis of data showed that communication, engineering, geography, history and psychology were attended by students with more diverse socioeconomic and demographic profiles. Thus, the self-administered questionnaire was preferably, but not exclusively, applied to students from these courses. All questionnaires were applied between April and May 2010.
About two-thirds of the respondents of the final instrument were in the first and second years of college. Almost 40% of the 424 respondents were enrolled as undergraduate students of psychology and biology. Approximately 60% were female, 60% were 18 to 21 years old, and almost all of them (90%) were single. Approximately half of them self-classified as white, 30% as mixed skin color and 15% as blacks. Approximately 40% had been admitted to college through an admission quota and 40% had parents with 13 or more years of schooling. The socioeconomic profile of this sample was higher, compared to the general population of the city of Rio de Janeiro, using the IEN distribution based on the 2000 Brazilian census. More than 70% of the respondents fell within the highest socioeconomic quintile for the population of the city of Rio de Janeiro.
With regard to the psychometric properties of the instrument, it was first carried out a description of the score distribution and relative frequencies of items on differential treatment attributed to discrimination by gender, age, skin color/race, type of admission to college and socioeconomic status.
Three combinations of items were then tested using an exploratory factor analysis: (1) only items on exposure to negative differential treatment; (2) a combination of items on differential treatment and discomfort caused by these experiences (positive responses were those reporting, at least, some discomfort); and (3) a combination of information on exposure to differential treatments and their attribution to discrimination (respondents who were discriminated against were those whose differential treatment experiences were attributed to discrimination). The motivations for the reported differential treatments were not an object of analysis and they will be addressed in future publications.
With regard to dimensional validity, the initial assumption was that all items reflected a single conceptual dimension.7 The first step of the factor analysis included Bartlett's test of sphericity and the Kaiser-Meyer-Olkin measure of sampling adequacy, which was performed for all items and for each one individually. Statistically significant p-values (p<0.05) in the Bartlett's test and measures greater than 0.5 in the Kaiser-Meyer-Olkin test indicated that we could proceed with the factor analysis.14,22 Polychoric transformation of the correlation matrix of items was performed to meet factor analysis assumptions. The resulting matrix was assessed using the principal axis factoring method to extract factors.22 The number of factors to be retained was determined by the magnitude of the eigenvalues, percent of variance explained and visual analysis of the scree plot.22
The discrimination score was calculated by summing up all its 18 items, so that higher scores indicated higher frequency of exposure to discrimination. Given that items were measured using a 4-point Likert scale (0, 1, 2, and 3), the final score could range between zero and 54. This score allowed to assess the instrument's construct validity based on comparisons of extreme groups and convergent validity tests. The analysis of extreme groups consisted of a comparison of the discrimination score distribution among groups with different "quantities" of the construct, i.e., population groups who are in theory more or less frequently discriminated against. It was hypothesized that self-reported blacks or mixed skin color, women, individuals who were older, poor and admitted through college admission quotas would score higher.4 The convergent validity assessment, which tests the correlation between the discrimination score and other measures to which it should be associated, was checked using estimates of association with alcohol use, smoking, common mental disorders and self-reported health status. These health behaviors and conditions have been associated to stress factors and experiences of discrimination in previous studies.25 Given the skewed distribution of the discrimination score, the Mann-Whitney U test and the Kruskal-Wallis test were used for these comparisons. The level of statistical significance was 5% for two-tailed tests. Two dimensions of reliability were assessed: internal consistency with Cronbach's alpha and test-retest by weighted kappa coefficients.
The study was approved by the Research Ethics Committees of both the institutions involved: Universidade Federal de Pelotas (process number 012/08) and Universidade do Estado do Rio de Janeiro (process number 0016.0.259.000-08). Participation at any step of the study was voluntary and all participants signed an informed consent form.
The qualitative study showed that the constructs of discrimination and prejudice are relevant and applicable within the sociocultural background studied. In general, the meanings attributed to discrimination in the focus groups were close to the concept of discrimination described in the study's theoretical framework. Experiences of discrimination were reported within the expected domains, except for housing, which was not mentioned by the focus groups. The domains of public and private services, affective-sexual relationships and family environment were added as they were relevant for students of the age group studied. Contrary to what was expected, the participants showed difficulty in rating their discriminatory experiences in a scale of intensity. They also reported discriminatory experiences with multiple motivations, indicating that the instrument should allow entering more than one reason for the same differential treatment experienced.
The panel of seven experts pointed out aspects of face and content validity, structure and wording of the preliminary set of items. At the end of this process, the preliminary set of items, which initially had 28 questions, consisted of 18 questions about discriminatory experiences (Table 1) and one question on witnessing differential treatment perpetrated against others.
Cognitive interviews showed that the instrument's instructions needed to be shorter, straightforward and more easy to understand, and that some items had to be reworded for consistent interpretation. These changes were mainly to clarify that the items were addressing differential treatments with a negative connotation only. These interviews also indicated that the wording should be simpler and more colloquial. The pilot study helped determining the average time for instrument completion, which ranged between 25 and 45 minutes. It also showed that the proposed logistics for field work was adequate with minimal interference with the students' schedule, so that there were no refusals to participate in the study.
As for the assessment of the instrument's psychometric properties, the results here described refer to the combination of items inquiring about exposure to differential treatments and the attribution of these events to discrimination as they showed the best psychometric performance. The discrimination score showed a right-skewed distribution. The mean, median and standard deviation of the score were 3.5, 2 and 4, respectively, ranging from zero to 25. Almost 75% of the respondents reported at least one episode of differential treatment attributed to discrimination. The frequency distribution of items in the instrument showed that 10 out of 18 items were given a positive answer by 10% or more of respondents. Items 1, 3, 5, 8, 9, 15, 17 and 18 had the lowest frequencies of positive answers. Low variability was also seen according to gender, age, skin color/race, type of college admission and socioeconomic status. The only exceptions were item 1, according to skin color/race and type of college admission; item 8, according to age and skin color/race; and item 18, according skin color/race, type of college admission and socioeconomic status.
Two-thirds (86/144) of the correlation coefficients among the 18 items about experiences of discrimination were greater than 0.3, ranging from 0.3 to 0.7. This correlation matrix showed a p<0.001 in the Bartlett's test of sphericity and a coefficient of 0.6 in the Kaiser-Meyer-Olkin test. Except for items 7, 8 and 14, the remaining ones showed a Kaiser-Meyer-Olkin coefficient greater 0.5, ranging between 0.5 and 0.9.
The exploratory factor analysis identified a single factor that showed a significantly higher eigenvalue (6.6) than the others, such as the second (1.4) and third (0.9) factors. In addition, the first factor was the only one to have exclusively positive loadings, all of them higher than 0.4 and most of them (17 out of 18 [94%]) ranging between 0.5 and 0.6. Half of the items (1, 3, 4, 7, 9, 12, 14, 15 and 18) loaded on the second and/or third factors, but their loadings were of lesser magnitude than those estimated for the first factor and had positive and negative signs, contrasting with what was theoretically predicted. The retention of only one factor was also supported by the analysis of the scree plot with an "elbow" in the transition between the first and second factors. The final factor solution, including the 18 original items and a single factor to be retained, is presented in Table 2. The percentage of variance explained by this solution was 56%, and the proportion of common variance not attributable to the factor (uniqueness) ranged between 0.5 and 0.7 for all items.
The instrument's internal consistency measured by Cronbach's alpha was 0.8 and the consecutive exclusion of items did not significantly change it (differences were around 0.01). The item-instrument and item-rest correlations ranged between 0.2 and 0.6. The test-retest reliability assessed through weighted kappa was greater than 0.5 for 14 of 18 items. Items 4, 5, 8 and 16 had coefficients of 0.3, 0.3, 0.2 and 0.1 respectively. In summary, item 8 showed the poorest psychometric performance with low relative frequency, low Kaiser-Meyer-Olkin coefficient and low test-retest reliability. All other items with little variability showed satisfactory results with regard to the other psychometric indicators mentioned.
The discrimination score was statistically higher among those self-reported with mixed and black skin color, females, those admitted through college admission quotas and those with lower socioeconomic status (Table 3). The score was also statistically higher among those who reported ever smoking (especially before the age of 17), those with common mental disorders and those who self-rated their general health status as regular/poor/very poor.
This study presents the first instrument to assess explicit personally-mediated discrimination, proposed outside the context of high-income countries. To our knowledge,3 previous instruments were developed exclusively in the U.S., with the exception of the Measure of Indigenous Racism Experiences, developed by Paradies & Cunningham in Australia.20 Context specificities must be taken into consideration since Brazilian social relations are rather different to the U.S.'s, even more so if racial issues are considered. Particularly, inexistence of open social and racial conflicts, cordiality and miscegenation have been reported to be outstanding sociologic features of the Brazilian society. Also, the racial classification system in Brazil has been regarded as contextually dependent, subjective and imprecise.17 The Brazilian color continuum is based on the assignment of social distinctions to various skin color tones and terminologies used to very specifically allocate individuals along a spectrum, ranging from black to white.13 There is also a close relationship between socioeconomic status and race in Brazil, such that socially rising blacks or mixed skin color may self-classify - and be socially accepted - as whites. In terms of discrimination, specifically racial discrimination, some authors have argued that Brazilians show a tendency not to engage in social conflicts. However, in social interactions in which power disputes are involved, racial discrimination may be manifested as way to resolve these conflicts and clearly demarcate social positions.11
In part, some of these issues were reflected in the development of the present instrument for assessing discrimination and the results here described. For instance, the association between race and socioeconomic status, as well as previous studies on the reporting of multiple types of discrimination,4 influenced the development of an instrument that allows respondents to inform on multiple motivations for differential treatments they have experienced. This approach allows to examining the relative impact on health outcomes of differential treatments with multiple motivations compared to those with a single one. This has been poorly investigated and there is limited evidence suggesting that different forms of discrimination tend to be equally harmful,21 but with potential to be even more health-damaging when experienced simultaneously.ª
The low variability of some instrument's items such as 1, 3, 17 and 18 could mean that these aspects are not a common expression of discrimination in Brazilian social interactions; alternatively, they may only be infrequent in our sample of college students. From a psychometric viewpoint,9 items with a low percentage of positive answers are potential candidates for exclusion as they do not help differentiating levels of exposure to discrimination. Future studies assessing this instrument in other population groups should consider the low variability of these specific items and re-examine their pertinence in the instrument.
In addition to producing information on different types of discrimination, another innovative aspect of the proposed instrument is that it may distinguish the effects of exposure to differential treatments of any kind from the attribution of these events to discrimination. During the qualitative phase of instrument development,4 we observed that, even though some participants reported experiences of differential treatment motivated by socially ascribed or acquired characteristics - which, in theory, all conform to the definition of an interpersonal discriminatory event - they did not attribute these experiences to discrimination. This led us to include a subitem in the instrument on the attribution of experiences of differential treatment to discrimination, which, according to Major et al18 (2002), has been used mainly in research on sexual violence against women. Studies have suggested it is the very experience of harmful events, such as unwanted sex, that negatively impacts indicators of well-being, not the attribution of these events to any type of discrimination. However, this finding is not consistent with Schimtt & Branscombe's24 (2002) claim that it is the perception of an individual as a victim of discrimination that negatively affects his or her well-being. It is thus necessary to explore whether these findings hold for other types of discrimination, besides sexual harassment - the instrument here presented could be used in large health surveys to address such a controversial topic.
With regard to the limitations of the present instrument, we recognize that explicit discrimination has not been the only type of discrimination discussed from a theoretical and empirical perspective. According to Blank et al's7 (2004) typology, there are also subtler and institutionalized forms of discrimination, which should also be measured for a more comprehensive assessment of their prevalence and health effects. Krieger et al16 (2010) recently showed that the unconscious perception of discrimination experiences also has an impact on health, particularly hypertension. This suggests that the associations between health conditions and discriminatory experiences explored through the present instrument reflect a limited aspect of a wider causal network involving other forms of manifestation of discrimination.
Another important point refers to the reference population used for the construction of the instrument. Even though students from undergraduate courses with diverse socioeconomic and demographic profiles took part in this study, they represent a small and specific segment of the Brazilian general population, with a relatively high socioeconomic status. Some items included in the instrument reflected this sociocultural background; for instance, questions about experiences of discrimination at school and college apply only to people who have attended school. Also, the choice for a self-administered questionnaire, a strategy that aimed to minimize interviewer effects on reporting of sensitive information, also limits its use in surveys that include either illiterate or poorly literate populations.
These and other issues must be taken into consideration when adapting the instrument for use in different populations in both national and international contexts. In new research contexts, those items that showed low variability, as well as inadequate psychometric indicators, could be reassessed, reformulated or even replaced by other items that have a similar position in the construct map. Further psychometric evaluations, including discriminant validation and more rigorous techniques, such as confirmatory factor analysis, are needed. This instrument was named EDE, acronym for "Escala de Discriminação Explícita", or Explicit Discrimination Scale, in English.
The full version of the EDE (Explicit Discrimination Scale) is available in the online version of this article at www.scielo.br/rsp
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João Luiz Bastos
Departamento de Saúde Pública
Universidade Federal de Santa Catarina
88010-970 Florianópolis, SC, Brasil
Research funded by Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (Process N. E-26/110.315/20).
Paper based on the doctoral thesis submitted by Bastos JL to Universidade Federal de Pelotas in 2010.
The authors declare no conflicts of interests.
a Frykman J. Discrimination: a threat to public health: final report of Health and Discrimination Project. Stockholm: National Institute of Public Health; 2006.